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Incremental Few-Shot Learning via Implanting and Compressing
Specifically, in the \textbf{Implanting} step, we propose to mimic the data distribution of novel classes with the assistance of data-abundant base set, so that a model could learn semantically-rich features that are beneficial for discriminating between the base and other unseen classes.
Generalized Iterative Super-Twisting Sliding Mode Control: A Case Study on Flexure-Joint Dual-Drive H-Gantry Stage
Mechatronic systems are commonly used in the industry, where fast and accurate motion performance is always required to guarantee manufacturing precision and efficiency.
Global Iterative Sliding Mode Control of an Industrial Biaxial Gantry System for Contouring Motion Tasks
This paper proposes a global iterative sliding mode control approach for high-precision contouring tasks of a flexure-linked biaxial gantry system.
Convex Parameterization and Optimization for Robust Tracking of a Magnetically Levitated Planar Positioning System
Magnetic levitation positioning technology has attracted considerable research efforts and dedicated attention due to its extremely attractive features.
Neural-iLQR: A Learning-Aided Shooting Method for Trajectory Optimization
Iterative linear quadratic regulator (iLQR) has gained wide popularity in addressing trajectory optimization problems with nonlinear system models.
